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| Das Gupta Decomposition× | Direct Standardization× | |
|---|---|---|
| Campo | Demografia | Demografia |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1993 | 2001 |
| Ideatore≠ | Prithwis Das Gupta | Classical demographic method (formalized by Preston, Heuveline & Guillot) |
| Tipo≠ | Multi-factor, multi-population decomposition of a difference between rates | Rate adjustment by reweighting to a standard population |
| Fonte seminale≠ | Das Gupta, P. (1993). Standardization and Decomposition of Rates: A User's Manual. U.S. Bureau of the Census, Current Population Reports P23-186. link ↗ | Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 9781557864512 |
| Alias | Das Gupta's method, Multi-factor rate decomposition, Standardization and decomposition of rates, Das Gupta Ayrıştırması | Directly standardized rate, Age-standardized rate, Direct method of standardization, Doğrudan Standardizasyon |
| Correlati | 4 | 4 |
| Sintesi≠ | Das Gupta decomposition is the general framework for standardizing and decomposing a difference between summary rates when several factors act at once and more than two populations must be compared. Developed by Prithwis Das Gupta and codified in his 1993 U.S. Census Bureau manual, it generalizes Kitagawa's two-population, single-factor decomposition to any number of multiplicatively or additively combined factors and any number of populations, producing factor effects that are exactly additive, symmetric, and internally consistent across every pairwise comparison. | Direct standardization is a demographic technique that makes summary rates comparable across populations by applying each population's group-specific rates — most often age-specific death or disease rates — to a single, common standard population structure. The resulting directly standardized rate answers a counterfactual question: what would the crude rate be if every population had the same age (or other) composition? It removes the confounding effect of differing population structure so that genuine differences in underlying risk can be compared on a level footing. |
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